Accenture North America Data Analytics and Visualization Job Simulation (October 2024)

Overview

This repository contains the work completed during the Accenture North America Data Analytics and Visualization Job Simulation on Forage in October 2024. The project involved advising a hypothetical social media client as a Data Analyst. I worked with CSV files related to content, reactions, and reaction types to analyze trends and provide strategic recommendations, including data sampling and modeling.

Project Deliverables

Key activities and deliverables include:

• Data Cleaning: Cleaned and organized the datasets using Google Sheets to remove inconsistencies and prepare them for analysis.
• Data Sampling: Applied data sampling techniques to ensure the datasets were representative and manageable for analysis.
• Data Analysis & Modeling: Performed analysis in Google Sheets to uncover key insights into content performance, user reactions, and engagement trends. Created models to better understand relationships between variables and forecast outcomes.
• Visualization & Reporting: Created charts and visual representations of the analysis in Google Sheets and Google Slides.
• Presentation: Developed a slide deck in Google Slides and recorded a video presentation using Loom to communicate the findings to the client and internal stakeholders.

Datasets

The project utilized three main datasets:

1. Content CSV - Information on various content types posted on the platform.
2. Reactions CSV - Data on user interactions with the content.
3. Reaction Types CSV - Categorization of different reaction types (e.g., likes, comments, shares).

Final Analysis File

• Final Analysis File - Contains the final insights and visualisations to perform data driven business decision.

Key Insights

The analysis generated key insights, including:

• Identification of content types that drive the highest engagement.
• Insights into how users react to different types of content.
• Data modeling to predict content performance based on reactions and other metrics.
• Summary on improving content strategies based on user reaction patterns and the model's predictions.

Tools & Technologies Used

• Google Sheets: For data cleaning, sampling, analysis, modeling, and creating visual charts.
• Google Slides: For preparing the presentation slides.
• Loom: For recording the video presentation.

Slide Deck and Video

• Slide Deck - Google Slides presentation summarizing the analysis.
• Watch the video - Loom video explaining key findings and recommendations.

Conclusion

Conclusion

This simulation provided hands-on experience in using data analytics, sampling, and modeling to inform business strategy. The insights and models derived from the analysis can help the client optimize content strategies and enhance user engagement.